Contaminant-Associated Disruption of the Skin Transcriptome in the Endangered St. Lawrence Estuary Beluga
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide The St. Lawrence Estuary (SLE) beluga ( Delphinapterus leucas ) population in Canada is Endangered, and endocrine disrupting contaminants, such as polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and other halogenated flame retardants, have been identified as a threat to the recovery of this population. Here, potential impacts of these contaminants on SLE beluga were evaluated by comparing skin transcriptome profiles and biological pathways between this population and a population less exposed to contaminants (Eastern Beaufort Sea) used as a reference. Differential gene expression analysis indicated potential seasonal or geography-related (Arctic vs temperate regions) effects on the skin transcriptome. Among the gene transcripts that were associated with Σ 31 PCB (123 genes), Σ 29 PBDE (198 genes), HBB (347 genes), and PBEB (126 genes) blubber concentrations, several were related to immune response pathways. In addition, 18 toxicology-related gene transcripts selected from the literature were correlated with organohalogen concentrations and were used to derive new threshold values in beluga skin for potential biological effects of ΣPCB (1,500 ng/g lw), ΣPBDE (52 ng/g lw), and two other flame retardants, i.e., HBB (1.2 ng/g lw) and PBEB (0.04 ng/g lw). Results suggest that exposure to these organohalogens pose a risk to the immune system of SLE beluga.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".